CN112835098B

CN112835098B - Method and device for predicting energy storage coefficient of weathered-crust karst reservoir

Info

Publication number: CN112835098B
Application number: CN202110008598.9A
Authority: CN
Inventors: 戴晓峰; 甘利灯; 张明; 姜晓宇; 杜本强; 隆辉; 牟川; 江林; 王浩
Original assignee: Petrochina Co Ltd
Current assignee: Petrochina Co Ltd
Priority date: 2021-01-05
Filing date: 2021-01-05
Publication date: 2024-03-01
Anticipated expiration: 2041-01-05
Also published as: CN112835098A

Abstract

The invention discloses a method and a device for predicting an energy storage coefficient of a weathered crust karst reservoir, wherein the method comprises the following steps: and extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted, and predicting to obtain the energy storage coefficient of the reservoir to be predicted by utilizing the conversion relation between the energy storage coefficient obtained after fitting and the seismic amplitude attribute value. According to the method, the energy storage coefficient of the weathered karst reservoir is directly predicted by fitting the conversion relation between the energy storage coefficient and the seismic amplitude attribute value, so that the accuracy of the energy storage coefficient prediction of the weathered karst reservoir can be improved.

Description

Method and device for predicting energy storage coefficient of weathered-crust karst reservoir

Technical Field

The invention relates to the technical field of geological exploration, in particular to a method and a device for predicting an energy storage coefficient of a weathered crust karst reservoir.

Background

This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.

The domestic deep sea-phase carbonate rock karst generally develops, and the weathered shell karst reservoir is mainly distributed in Erdos, tarim, sichuan basin and the like in China, and is one of main gas-producing layers of China sea-phase oil-gas-bearing basin. The earthquake prediction of the weathered karst reservoir mainly adopts an earthquake attribute or earthquake inversion method to predict the earthquake phase, thickness, porosity, oil-gas property and sedimentary facies of the weathered karst reservoir, predicts the distribution range of the favorable reservoir, and supports well position deployment of exploration and development.

Factors influencing the capacity of weathered shell karst reservoirs are numerous, with the two key factors being thickness and porosity of the weathered shell karst reservoir. Wherein the size of the porosity determines how much fluid the reservoir contains per unit volume, the greater the porosity, the more fluid the pore space contains; the greater the reservoir thickness, the higher the hydrocarbon production. Clearly neither a single thickness nor porosity reflects well the potential capacity of the reservoir. In the oil and gas industry, the energy storage coefficient is the product of reservoir thickness and porosity and hydrocarbon saturation, often expressed as (hφSg) or (hφso). The energy storage coefficient comprehensively reflects the characteristics of the thickness, scale, shape, physical property, grade and the like of the reservoir, the size of the energy storage coefficient is closely related to reserves and productivity, and the energy storage coefficient is a good parameter for oil gas enrichment and productivity prediction. Thus, the energy storage coefficient is more suitable for capacity prediction of low pore hypotonic reservoirs formed by weathered shell karst than a single porosity or reservoir thickness.

At present, few examples of utilizing seismic data to predict the energy storage coefficient are mainly to respectively predict the porosity and the thickness of a reservoir by adopting the seismic data and then calculate the energy storage coefficient after multiplying the porosity and the thickness. For example, in 2004, daylily selects seismic attributes, predicts the porosity and effective thickness of a reservoir respectively, and multiplies the two to obtain an energy storage coefficient distribution prediction graph. In 2004, xie Fang obtained the thickness and porosity of the reservoir layer on the plane by inversion, and calculated the energy storage coefficient by combining the two. In 2017, gu Yuewei applied model iterative inversion to predict reservoir thickness, predicted porosity based on velocity inversion, and finally calculated the mathematical product of thickness and porosity result to obtain energy storage coefficient.

In recent years, seismic facies interpretation based on seismic profiles become a main method for predicting karst reservoirs, namely, different seismic waveform characteristics corresponding to different types of reservoirs are summarized according to reflection characteristics of known wells and well-side seismic channels thereof and statistical analysis, and the method is used for predicting the capacity of the karst reservoirs. For example, in 2018, the Xiaofusen uses high-resolution seismic data to develop seismic response characteristics of typical wells of different reservoir composition types and high-yield well seismic pattern researches, divides four sections of weathered shell karst reservoirs into 3 types of seismic patterns, and qualitatively predicts the production energy of the karst reservoirs.

However, in the prior art, the energy storage coefficient of the weathered karst reservoir is predicted indirectly through parameters such as porosity, thickness and the like, or the energy production capacity of the weathered karst reservoir is predicted qualitatively, so that the prediction accuracy of the energy storage coefficient of the weathered karst reservoir is not high.

Disclosure of Invention

The embodiment of the invention provides a method for predicting the energy storage coefficient of a weathered crust karst reservoir, which is used for directly realizing the energy storage coefficient prediction of the weathered crust karst reservoir and improving the energy storage coefficient prediction precision, and comprises the following steps:

extracting an earthquake amplitude attribute value of earthquake data of a reservoir to be predicted;

And predicting to obtain the energy storage coefficient of the reservoir to be predicted by using the conversion relation between the energy storage coefficient obtained after fitting and the seismic amplitude attribute value.

The embodiment of the invention also provides an energy storage coefficient prediction device of the weathered shell karst reservoir, which is used for directly realizing the energy storage coefficient prediction of the weathered shell karst reservoir and improving the accuracy of the energy storage coefficient prediction, and comprises the following components:

the amplitude attribute extraction module is used for extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted;

and the energy storage coefficient prediction module is used for predicting and obtaining the energy storage coefficient of the reservoir to be predicted by utilizing the conversion relation between the energy storage coefficient obtained after fitting and the seismic amplitude attribute value.

The embodiment of the invention also provides computer equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the energy storage coefficient prediction method of the weathered shell karst reservoir is realized when the processor executes the computer program.

The embodiment of the invention also provides a computer readable storage medium, which stores a computer program for executing the method for predicting the energy storage coefficient of the weathering crust karst reservoir.

In the embodiment of the invention, the energy storage coefficient of the reservoir to be predicted is obtained by extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted and predicting by utilizing the conversion relation between the energy storage coefficient obtained after fitting and the seismic amplitude attribute value. According to the embodiment of the invention, the energy storage coefficient of the weathered shell karst reservoir is directly predicted by fitting the conversion relation between the energy storage coefficient and the seismic amplitude attribute value, so that the accuracy of the energy storage coefficient prediction of the weathered shell karst reservoir can be improved.

Drawings

In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:

FIG. 1 is a flowchart of an implementation of a method for predicting an energy storage coefficient of a weathered shell karst reservoir according to an embodiment of the present invention;

FIG. 2 is a flowchart of another implementation of a method for predicting an energy storage coefficient of a weathered shell karst reservoir according to an embodiment of the present invention;

FIG. 3 is a flowchart of an implementation of a conversion relationship between a fitted energy storage coefficient and an earthquake amplitude attribute value in the energy storage coefficient prediction method of a weathered shell karst reservoir according to an embodiment of the present invention;

FIG. 3-1 is a schematic view of a three-dimensional forward seismic recording of a target sample reservoir according to an embodiment of the present invention;

FIG. 3-2 is a schematic view of a scatter-intersection of target sample reservoir energy storage coefficients and seismic amplitude attribute values provided by an embodiment of the present invention;

FIG. 4 is another implementation flowchart of a conversion relationship between a fit energy storage coefficient and an earthquake amplitude attribute value in an energy storage coefficient prediction method for a weathered shell karst reservoir according to an embodiment of the present invention;

FIG. 4-1 is a schematic diagram of a three-dimensional forward seismic record after the target sample reservoir is unshielded according to an embodiment of the present invention;

FIG. 5 is a flowchart illustrating implementation of step 301 in a method for predicting an energy storage coefficient of a weathered shell karst reservoir according to an embodiment of the present invention;

fig. 6 is a flowchart illustrating implementation of step 503 in a method for predicting an energy storage coefficient of a weathered shell karst reservoir according to an embodiment of the present invention;

FIG. 6-1 is a schematic diagram of a three-dimensional wave impedance model of a target sample reservoir according to an embodiment of the present invention;

FIG. 7 is a flowchart of another implementation of step 503 in a method for predicting an energy storage coefficient of a weathered shell karst reservoir according to an embodiment of the present invention;

FIG. 8 is a flowchart illustrating an implementation of step 302 in a method for predicting an energy storage coefficient of a weathered shell karst reservoir according to an embodiment of the present invention;

FIG. 9 is a functional block diagram of an energy storage coefficient prediction device for a weathered shell karst reservoir according to an embodiment of the present invention;

FIG. 10 is another functional block diagram of an energy storage coefficient prediction apparatus for a weathered shell karst reservoir according to an embodiment of the present invention;

FIG. 11 is a block diagram of a conversion relationship between a fitted energy storage coefficient and an earthquake amplitude attribute value in an energy storage coefficient prediction device for a weathered shell karst reservoir according to an embodiment of the present invention;

FIG. 12 is another block diagram of a conversion relationship between a fitted energy storage coefficient and an seismic amplitude attribute value in an energy storage coefficient prediction apparatus for a weathered shell karst reservoir according to an embodiment of the present invention;

FIG. 13 is a block diagram illustrating a seismic record determination module 1101 in a device for predicting energy storage coefficients of a weathered shell karst reservoir according to an embodiment of the present invention;

fig. 14 is a block diagram of a model construction unit 1303 in an energy storage coefficient prediction apparatus for a weathered shell karst reservoir according to an embodiment of the present invention;

fig. 15 is another block diagram of a model construction unit 1303 in the device for predicting an energy storage coefficient of a weathered shell karst reservoir according to the embodiment of the present invention;

Fig. 16 is a block diagram illustrating a sample seismic amplitude extraction module 1102 in an energy storage coefficient prediction apparatus for a weathered karst reservoir according to an embodiment of the present invention.

Detailed Description

For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention will be described in further detail with reference to the accompanying drawings. The exemplary embodiments of the present invention and their descriptions herein are for the purpose of explaining the present invention, but are not to be construed as limiting the invention.

Fig. 1 shows a flow of implementation of the method for predicting the energy storage coefficient of the weathered shell karst reservoir according to the embodiment of the present invention, and for convenience of description, only the portions relevant to the embodiment of the present invention are shown, and the details are as follows:

as shown in fig. 1, a method for predicting an energy storage coefficient of a weathered shell karst reservoir includes:

step 101, extracting an earthquake amplitude attribute value of earthquake data of a reservoir to be predicted;

and 102, predicting to obtain the energy storage coefficient of the reservoir to be predicted by using the conversion relation between the energy storage coefficient obtained after fitting and the seismic amplitude attribute value.

The non-integral surface of the weathering crust is preferably deposited for a longer period of time and the erosion effect is relatively strong. The contemporaneous or quasi-contemporaneous karst effect caused by short periodic exposure is difficult to form karst with large influence depth, large scale and wide distribution, is insufficient for forming karst non-integration, has small karst reservoir thickness and is difficult to identify earthquake.

The embodiment of the invention is exemplified by a karst reservoir (namely a target sample reservoir) of a light shadow group of a Shake denier system in Sichuan basin and Chuan-in region. The lamp shadow group is lifted under the influence of tung bay movement and is subjected to two-period atmospheric fresh water leaching modification with different degrees, so that a four-section lamp and two-section lamp two-set weathered shell karst reservoir is formed. Early stage Wu Shi, on the basis of the ancient topography of the high and low fluctuation, deposits black gray carbonaceous shale and pink sandy shale of the qianwu system qianzhusi temple group, and the chilly system and the qianqianqianqi system are in non-integrated contact relation. The top stratum of the lamp shadow group is exposed on the ground surface, and the carbonate stratum is subjected to long-term strong corrosion action through the corrosion leaching of the atmospheric fresh water, so that a large number of corrosion holes are formed, the physical property of the reservoir is good, and a high-quality weathered shell karst reservoir is formed at the upper four sections of the lamp.

When the energy storage coefficient of the weathered karst reservoir is predicted, firstly, the seismic amplitude attribute value of the reservoir seismic data to be predicted is extracted. The reservoir seismic data to be predicted is the seismic data used for actual production to be processed. After the seismic amplitude attribute value of the reservoir seismic data to be predicted is extracted, the energy storage coefficient of the reservoir to be predicted is predicted by utilizing the conversion relation between the energy storage coefficient obtained after fitting and the seismic amplitude attribute value, so as to obtain the energy storage coefficient of the reservoir to be predicted. The conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting reflects the association relation between the energy storage coefficient and the seismic amplitude attribute value, namely, under the condition that the seismic amplitude attribute value is known, the energy storage coefficient of the reservoir to be predicted can be obtained through the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting.

Fig. 2 shows another implementation flow of the method for predicting the energy storage coefficient of the weathered shell karst reservoir according to the embodiment of the present invention, and for convenience of description, only the portions relevant to the embodiment of the present invention are shown, and the details are as follows:

in an embodiment of the present invention, in order to further improve the prediction accuracy of the energy storage coefficient, as shown in fig. 2, on the basis of the method steps shown in fig. 1, the method for predicting the energy storage coefficient of the weathered karst reservoir further includes:

step 201, performing strong reflection removal shielding treatment on the seismic data of the reservoir to be predicted to obtain the seismic data of the reservoir to be predicted after the shielding;

step 101, extracting a seismic amplitude attribute value of seismic data of a reservoir to be predicted, including:

Step 202, extracting seismic amplitude attribute values of the seismic data of which the reservoir to be predicted is unmasked.

Because when the karst reservoir thickness is smaller, the amplitude rule at the bottom of the reservoir is not obvious under the tuning effect of strong reflection of the weathered crust, and the karst reservoirs with different thicknesses and porosities can respectively correspond to strong reflection wave peaks, zero point weak reflection wave peaks or wave troughs. It is difficult to track the reservoir bottom surface directly through forward seismic recording, and the correlation of seismic reflection energy, reservoir thickness, porosity is poor, reservoir prediction is difficult.

Therefore, before the seismic amplitude attribute value of the seismic data of the reservoir to be predicted is extracted, the seismic data of the reservoir to be predicted can be subjected to the anti-strong reflection shielding treatment, and then the seismic amplitude attribute value of the seismic data of the reservoir to be predicted after the shielding treatment is extracted. The true seismic reflection of the unshielded karst reservoir is recovered, the bottom surface of the reservoir corresponds to the peak reflection, and the larger the thickness of the reservoir, the stronger the peak energy, and the larger the porosity, the stronger the peak energy.

The extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted may specifically include: acquiring seismic data of a reservoir to be predicted; acquiring seismic wavelets of a target sample reservoir according to the seismic data of the reservoir to be predicted; constructing a three-dimensional wave impedance model of the reservoir to be predicted; and carrying out seismic forward modeling by using the constructed three-dimensional wave impedance model and the seismic wavelet of the reservoir to be predicted, obtaining the three-dimensional forward seismic record of the reservoir to be predicted, and further extracting the seismic amplitude attribute value of the three-dimensional forward seismic record of the reservoir to be predicted.

In the embodiment of the invention, the seismic data of the reservoir to be predicted is subjected to the anti-strong reflection shielding treatment to obtain the seismic data of the reservoir to be predicted after the shielding, and the seismic amplitude attribute value of the seismic data of the reservoir to be predicted after the shielding is extracted, so that the prediction precision of the energy storage coefficient can be further improved.

Fig. 3 shows a flow of implementing a conversion relationship between a fit energy storage coefficient and a seismic amplitude attribute value in the method for predicting an energy storage coefficient of a weathered shell karst reservoir according to an embodiment of the present invention, and for convenience of description, only the portions relevant to the embodiments of the present invention are shown, which are described in detail below:

in an embodiment of the present invention, to further improve the prediction accuracy of the energy storage coefficient, as shown in fig. 3, fitting the conversion relationship between the energy storage coefficient and the seismic amplitude attribute value includes:

step 301, determining a three-dimensional forward seismic record of a target sample reservoir according to seismic data of the target sample reservoir;

step 302, extracting a seismic amplitude attribute value of a three-dimensional forward seismic record of a target sample reservoir and a inline sequence number value and a crossline sequence number value corresponding to the seismic amplitude attribute value;

step 303, determining an energy storage coefficient of the target sample reservoir according to the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value;

And 304, performing intersection analysis on the energy storage coefficient and the seismic amplitude attribute value of the target sample reservoir, and fitting to construct a conversion relation between the energy storage coefficient and the seismic amplitude attribute value.

When the conversion relation between the energy storage coefficient and the seismic amplitude attribute value is fitted, firstly, seismic data of a target sample reservoir are acquired, for example, seismic data of a karst reservoir of a lamp shadow group of the upper earthquake in Sichuan basin and Chuan-in area are acquired from an oil field. And then determining the three-dimensional forward seismic record of the target sample reservoir according to the seismic data of the target sample reservoir. Fig. 3-1 shows a three-dimensional forward seismic record of a karst reservoir (target sample reservoir) of a lamp shadow group in a light shadow group in a region in the middle of Sichuan basin, provided by an embodiment of the invention.

And then extracting a seismic amplitude attribute value Amp (i, j) from the three-dimensional forward seismic record of the target sample reservoir, wherein i and j respectively represent a inline sequence number value and a crossline sequence number value corresponding to the seismic amplitude attribute value.

After the seismic amplitude attribute value and the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value are extracted, the energy storage coefficient of the target sample reservoir can be determined based on the geological model of the weathered shell karst reservoir by using the following formula:

Wherein,and the energy storage coefficient of the target sample reservoir is represented, and i and j respectively represent a inline sequence number value and a crossline sequence number value corresponding to the seismic amplitude attribute value of the target sample reservoir.

After the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir and the energy storage coefficient of the target sample reservoir are respectively obtained, intersection analysis is carried out on the energy storage coefficient of the target sample reservoir and the seismic amplitude attribute value, and a scattered point intersection graph of the energy storage coefficient and the seismic amplitude attribute value is obtained. Fig. 3-2 shows a scatter plot of energy storage coefficients and seismic amplitude attribute values of a target sample reservoir provided by an embodiment of the present invention, wherein an X-axis is the seismic amplitude attribute value, and a Y-axis is the energy storage coefficient, and it can be seen from fig. 3-2 that a good linear relationship exists between the energy storage coefficients and the seismic amplitude attribute values, and accordingly, the scatter plot is used to fit a conversion relationship between the energy storage coefficients and the seismic amplitude attribute values, so as to obtain a conversion relationship between the energy storage coefficients and the seismic amplitude attribute values, which may be:

wherein,represents the energy storage coefficient, amp represents the seismic amplitude attribute value, R ² Representing the variance.

According to the embodiment of the invention, the three-dimensional forward seismic record of the target sample reservoir is determined according to the seismic data of the target sample reservoir, then the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir and the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value are extracted, then the energy storage coefficient of the target sample reservoir is determined according to the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value, finally the energy storage coefficient of the target sample reservoir and the seismic amplitude attribute value are subjected to intersection analysis, the conversion relation between the energy storage coefficient and the seismic amplitude attribute value is constructed by fitting, the association relation between the energy storage coefficient and the seismic amplitude attribute value can be accurately reflected by the obtained conversion relation by fitting, the energy storage coefficient is predicted by utilizing the conversion relation between the energy storage coefficient obtained by fitting and the seismic amplitude attribute value, and the prediction accuracy of the energy storage coefficient can be further improved.

Fig. 4 shows another implementation flow of the conversion relationship between the fit energy storage coefficient and the seismic amplitude attribute value in the energy storage coefficient prediction method of the weathered shell karst reservoir according to the embodiment of the present invention, and for convenience of description, only the relevant parts of the embodiment of the present invention are shown, and the details are as follows:

in an embodiment of the present invention, in order to further improve the prediction accuracy of the energy storage coefficient, as shown in fig. 4, on the basis of the method steps shown in fig. 3, the fitting of the conversion relationship between the energy storage coefficient and the seismic amplitude attribute value further includes:

step 401, performing strong reflection removal shielding treatment on the three-dimensional forward seismic record of the target sample reservoir along the weathered shell to obtain the three-dimensional forward seismic record of the target sample reservoir after the shielding;

step 302, extracting a seismic amplitude attribute value of a three-dimensional forward seismic record of a target sample reservoir and a inline sequence number value and a crossline sequence number value corresponding to the seismic amplitude attribute value, including:

step 402, extracting the seismic amplitude attribute value of the three-dimensional forward seismic record after the target sample reservoir is unmasked and the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value.

Therefore, before the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir is extracted, the three-dimensional forward seismic record of the target sample reservoir can be subjected to strong reflection removal shielding treatment, and then the seismic amplitude attribute value of the three-dimensional forward seismic record after the target sample reservoir is subjected to shielding is extracted.

Fig. 4-1 shows a three-dimensional forward seismic record of a target sample reservoir after unshielded, and it can be seen from fig. 4-1 that the true seismic reflection of the unshielded karst reservoir is recovered, the bottom surfaces of the reservoirs are reflected by corresponding peaks, and the greater the thickness of the reservoir, the greater the peak energy and the greater the porosity, the greater the peak energy.

In the embodiment of the invention, the three-dimensional forward seismic record of the target sample reservoir is subjected to strong reflection shielding treatment along the weathered shell to obtain the three-dimensional forward seismic record of the target sample reservoir after the shielding, the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir after the shielding is extracted, and the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value are extracted, so that the prediction precision of the energy storage coefficient can be further improved through the strong reflection shielding treatment.

Fig. 5 shows a flow of implementation of step 301 in the method for predicting an energy storage coefficient of a weathered shell karst reservoir according to the embodiment of the present invention, and for convenience of description, only the portions relevant to the embodiment of the present invention are shown, which are described in detail below:

In one embodiment of the present invention, to improve the accuracy of determining the three-dimensional forward seismic record of the target sample reservoir, as shown in fig. 5, step 301 of determining the three-dimensional forward seismic record of the target sample reservoir from the seismic data of the target sample reservoir includes:

step 501, obtaining seismic data of a target sample reservoir;

step 502, obtaining seismic wavelets of a target sample reservoir according to seismic data of the target sample reservoir;

step 503, constructing a three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity and time;

and 504, performing seismic forward modeling by using the constructed three-dimensional wave impedance model and the seismic wavelets of the target sample reservoir to obtain a three-dimensional forward seismic record of the target sample reservoir.

When determining the three-dimensional forward seismic record of the target sample reservoir, firstly acquiring the seismic data of the target sample reservoir, further extracting the seismic wavelet of the seismic data of the target sample reservoir, and then constructing a three-dimensional wave impedance model of the target sample reservoir, wherein the three-dimensional wave impedance model of the target sample reservoir is a three-dimensional wave impedance model related to reservoir thickness, reservoir porosity and time. After the seismic wavelet and the three-dimensional wave impedance model of the target sample reservoir are respectively obtained, the seismic wavelet and the three-dimensional wave impedance model of the target sample reservoir are convolved to perform seismic forward modeling, and a three-dimensional forward seismic record (namely, figure 3-1) of the target sample reservoir is obtained.

In the embodiment of the invention, firstly, the seismic data of the target sample reservoir is obtained, then the seismic wavelet of the target sample reservoir is obtained according to the seismic data of the target sample reservoir, then the three-dimensional wave impedance model of the target sample reservoir about the reservoir thickness, the reservoir porosity and the time is constructed, finally, the three-dimensional wave impedance model and the seismic wavelet of the constructed target sample reservoir are utilized to perform seismic forward modeling, and the three-dimensional forward seismic record of the target sample reservoir is obtained.

Fig. 6 shows a flow of implementation of step 503 in the method for predicting an energy storage coefficient of a weathered shell karst reservoir according to the embodiment of the present invention, and for convenience of description, only the portions relevant to the embodiment of the present invention are shown, which is described in detail below:

in one embodiment of the present invention, to improve the accuracy of constructing the three-dimensional wave impedance model and further improve the prediction accuracy of the energy storage coefficient, as shown in fig. 6, in step 503, constructing the three-dimensional wave impedance model of the target sample reservoir with respect to the reservoir thickness, the reservoir porosity and the time includes:

Step 601, acquiring logging data of a target sample reservoir;

step 602, determining the average wave impedance of the overlying strata and the average wave impedance of the underlying carbonate strata in the target sample reservoir by using the logging data of the target sample reservoir;

step 603, determining wave impedance corresponding to weathered crust karst reservoirs with different porosities in the target sample reservoir through petrophysical analysis by using logging data of the target sample reservoir;

step 604, establishing a three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity and time according to the average wave impedance of the overlying strata in the target sample reservoir and the average wave impedance of the underlying carbonate strata and the wave impedances of the weathered crust karst reservoirs of different porosities in the target sample reservoir.

When a three-dimensional wave impedance model of a target sample reservoir is constructed, logging data of the target sample reservoir, which comprises a sound wave time difference, a density curve, reservoir parameters and the like, is firstly obtained.

In the embodiment of the invention, the target sample reservoir light shadow set top weathering crust upper covering stratum (cover layer) is a lower cold trojan system bamboo temple set stratum, and the lower section is dark gray, black gray mudstone and black carbonaceous shale. Below the weathered crust is a karst reservoir, and wind The crust-forming underburden stratum (carbonate stratum) is a lamp shadow group carbonate stratum and mainly comprises gray and gray dolomite. The target sample reservoir thus includes overburden, karst reservoir, and underburden. Further, the logging data of the target sample reservoir is used for carrying out statistical analysis, and the average wave impedance of the mud shale of the Hanwu system bamboo temple group under the overlying stratum is calculated and determined to be 10000m/s multiplied by g/cm ³ And the average wave impedance of the carbonate rock of the stratum under the weathering crust is 13800m/s multiplied by g/cm ³ . Further, by using logging data of the target sample reservoir, wave impedance corresponding to the weathered karst reservoirs with different porosities in the target sample reservoir is calculated through a petrophysical analysis method.

After the average wave impedance of the overlying strata and the average wave impedance of the underlying carbonate strata in the target sample reservoir and the wave impedance corresponding to the weathered crust karst reservoir with different porosities in the target sample reservoir are obtained respectively, a three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity and time is built based on the average wave impedance of the overlying strata and the average wave impedance of the underlying carbonate strata in the target sample reservoir and the wave impedance corresponding to the weathered crust karst reservoir with different porosities in the target sample reservoir.

FIG. 6-1 shows a three-dimensional wave impedance model of a target sample reservoir provided by an embodiment of the present invention, with the inline direction being reservoir thickness, increasing gradually from 0 to 30 meters; the cross-line direction is porosity, varying from 0% to 10%; the Z direction is time depth and the sampling rate is 1ms. FIG. 6-1 shows a weathering crust surface at a time depth of 20ms, a mudstone formation (overburden formation) with a stable thickness above the weathering crust, and a wave impedance of 10000m/s×g/cm ³ The method comprises the steps of carrying out a first treatment on the surface of the A karst reservoir layer is arranged below the weathering crust, and the change range of the reservoir wave impedance with the porosity ranging from 0% to 10% is 10900-13800 m/s multiplied by g/cm ³ The method comprises the steps of carrying out a first treatment on the surface of the The lowest part is carbonate non-reservoir stratum (underburden stratum) with wave impedance of 13800m/s multiplied by g/cm ³ 。

In the embodiment of the invention, logging data of a target sample reservoir are firstly obtained, then the logging data of the target sample reservoir are used for determining the average wave impedance of an overlying stratum and the average wave impedance of an underlying carbonate stratum in the target sample reservoir, then the logging data of the target sample reservoir are used for determining the wave impedance corresponding to weathering crust karst reservoirs with different porosities in the target sample reservoir through petrophysical analysis, and finally the three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity and time is established according to the average wave impedance of the overlying stratum and the average wave impedance of the underlying carbonate stratum in the target sample reservoir and the wave impedance corresponding to weathering karst reservoirs with different porosities in the target sample reservoir, and the accuracy of constructing the three-dimensional wave impedance model can be improved by constructing the three-dimensional wave impedance model with respect to reservoir thickness, reservoir porosity and time, so that the prediction accuracy of the energy storage coefficient is improved.

Fig. 7 shows another implementation flow of step 503 in the method for predicting the energy storage coefficient of the weathered shell karst reservoir according to the embodiment of the present invention, and for convenience of description, only the portion relevant to the embodiment of the present invention is shown, which is described in detail below:

in an embodiment of the present invention, in order to further improve the accuracy of constructing the three-dimensional wave impedance model, as shown in fig. 7, step 503, based on the method steps shown in fig. 6, constructs a three-dimensional wave impedance model of the target sample reservoir with respect to the reservoir thickness, the reservoir porosity and the time, and further includes:

step 701, determining a reservoir thickness maximum value and a porosity maximum value of a weathered shell karst reservoir in a target sample reservoir using log data of the target sample reservoir.

The three-dimensional wave impedance model of the target sample reservoir takes the reservoir thickness variation direction as a longitudinal line direction, the reservoir porosity variation direction as a transverse line direction and the time variation direction as a longitudinal line direction;

the reservoir thickness of the weathered shell karst reservoir in the target sample reservoir is gradually changed from zero to a reservoir thickness maximum in the inline direction, and the porosity of the weathered shell karst reservoir in the target sample reservoir is gradually changed from zero to a porosity maximum in the inline direction.

Determining a karst reservoir thickness maximum h using log data of a target sample reservoir based on regional geology awareness of a weathered karst reservoir _max And a porosity maximum value phi _max . The seismic grid of the three-dimensional wave impedance model of the target sample reservoir is set as: the direction of the inline is the thickness variation direction of the reservoir; the transverse line direction is the porosity change direction of the reservoir; the Z direction is the time direction. And the three-dimensional wave impedance model of the target sample reservoir is a 3-layer wave impedance model from top to bottom along the regolith. An overlying stratum with stable and uniform thickness is arranged above the weathering crust; a karst reservoir layer is arranged below the weathering crust, and the thickness of the corresponding reservoir layer along the direction of the inline line is from 0 to h _max The corresponding reservoir porosity in the crossline direction varies from 0 to phi _max The method comprises the steps of carrying out a first treatment on the surface of the Below the karst reservoir is a homogeneous carbonate non-reservoir underburden. In the Sichuan basin embodiment, the karst reservoir thickness values are counted according to the existing actual drilling results in the research area, and the maximum value of the karst reservoir thickness is determined to be 30 meters and the maximum porosity is determined to be 10 percent.

In the embodiment of the invention, the maximum reservoir thickness and the maximum porosity of the wind-driven shell karst reservoir in the target sample reservoir are determined by using the logging data of the target sample reservoir, so that the accuracy of constructing the three-dimensional wave impedance model can be further improved, and the prediction accuracy of the energy storage coefficient is further improved.

Fig. 8 shows a flow of implementation of step 302 in the method for predicting an energy storage coefficient of a weathered shell karst reservoir according to an embodiment of the present invention, and for convenience of description, only the portions relevant to the embodiment of the present invention are shown, which is described in detail below:

in an embodiment of the present invention, in order to improve accuracy of extracting the seismic amplitude attribute value and further improve prediction accuracy of the energy storage coefficient, as shown in fig. 8, step 302 of extracting the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir and the inline serial number value and the crossline serial number value corresponding to the seismic amplitude attribute value includes:

step 801, determining an effective seismic response time window of a target sample reservoir according to a three-dimensional forward seismic record of the target sample reservoir; the effective earthquake response time window of the target sample reservoir is the time length of the weathering crust from the corresponding peak reflection bottom of the reservoir on the earthquake path with the maximum reservoir thickness and the maximum porosity;

step 802, extracting a seismic amplitude attribute value and a inline sequence number value and a crossline sequence number value corresponding to the seismic amplitude attribute value along an effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir.

When extracting the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir, firstly determining the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir. The effective earthquake response time window of the target sample reservoir is the time length of the weathering crust from the corresponding peak reflection bottom of the reservoir on the earthquake channel where the reservoir thickness maximum value and the porosity maximum value are located. Fig. 4-1 is a three-dimensional forward seismic record of a target sample reservoir after unshielded according to an embodiment of the present invention, and as can be seen from fig. 4-1, the time range corresponding to the seismic peak reflection of different karst reservoirs is 20-39 ms, so that the effective seismic response time window of the reservoir is determined to be from weathered crust to weathered crust downward 19ms.

After determining the effective seismic response time window of the target sample reservoir, extracting a seismic amplitude attribute value Amp (i, j) along the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir. Wherein i and j respectively represent the inline sequence number value and the inline sequence number value corresponding to the seismic amplitude attribute value.

According to the method and the device, the effective earthquake response time window of the target sample reservoir is determined according to the three-dimensional forward earthquake records of the target sample reservoir, then the earthquake amplitude attribute value, the inline sequence number value and the crossline sequence number value corresponding to the earthquake amplitude attribute value are extracted along the effective earthquake response time window of the target sample reservoir according to the three-dimensional forward earthquake records of the target sample reservoir, the earthquake amplitude attribute value is extracted along the effective earthquake response time window, the accuracy of extracting the earthquake amplitude attribute value can be improved, and the prediction accuracy of the energy storage coefficient is further improved.

The embodiment of the invention also provides an energy storage coefficient prediction device for the weathered karst reservoir, as described in the following embodiment. Because the principle of solving the problems by the devices is similar to that of the method for predicting the energy storage coefficient of the weathered karst reservoir, the implementation of the devices can be referred to the implementation of the method, and the repeated parts are not repeated.

Fig. 9 shows functional modules of the energy storage coefficient prediction device for a weathered shell karst reservoir according to the embodiment of the present invention, and for convenience of explanation, only the portions relevant to the embodiment of the present invention are shown, and the details are as follows:

referring to fig. 9, each module included in the device for predicting the energy storage coefficient of the weathered karst reservoir is configured to perform each step in the corresponding embodiment of fig. 1, and specifically please refer to fig. 1 and the related description in the corresponding embodiment of fig. 1, which are not repeated herein. In the embodiment of the invention, the energy storage coefficient prediction device of the weathered crust karst reservoir comprises an amplitude attribute extraction module 901 and an energy storage coefficient prediction module 902.

The amplitude attribute extraction module 901 is configured to extract a seismic amplitude attribute value of seismic data of a reservoir to be predicted.

And the energy storage coefficient prediction module 902 is configured to predict and obtain an energy storage coefficient of the reservoir to be predicted by using a conversion relationship between the energy storage coefficient obtained after fitting and the seismic amplitude attribute value.

In the embodiment of the invention, the amplitude attribute extraction module 901 is used for extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted, and the energy storage coefficient prediction module 902 predicts and obtains the energy storage coefficient of the reservoir to be predicted by using the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained after fitting. According to the embodiment of the invention, the energy storage coefficient of the weathered shell karst reservoir is directly predicted by fitting the conversion relation between the energy storage coefficient and the seismic amplitude attribute value, so that the accuracy of the energy storage coefficient prediction of the weathered shell karst reservoir can be improved.

Fig. 10 shows another functional module of the weathered shell karst reservoir energy storage coefficient prediction apparatus according to the embodiment of the present invention, and for convenience of explanation, only the portions relevant to the embodiment of the present invention are shown, and the details are as follows:

in an embodiment of the present invention, in order to further improve the prediction accuracy of the energy storage coefficient, referring to fig. 10, each unit included in the energy storage coefficient prediction device of the weathered karst reservoir is used to perform each step in the corresponding embodiment of fig. 2, and specifically please refer to fig. 2 and the related description in the corresponding embodiment of fig. 2, which are not repeated herein. In the embodiment of the present invention, on the basis of the functional module shown in fig. 9, the device for predicting the energy storage coefficient of the weathered karst reservoir further includes a de-masking processing module 1001.

The demasking processing module 1001 is configured to perform demapping processing on the seismic data of the reservoir to be predicted, so as to obtain the seismic data of the reservoir to be predicted after demapping.

The amplitude attribute extraction module 901 is further configured to extract a seismic amplitude attribute value of the seismic data after the reservoir to be predicted is unmasked.

In the embodiment of the invention, the demasking processing module 1001 performs the demasking processing on the seismic data of the reservoir to be predicted to obtain the seismic data of the reservoir to be predicted after demasking, and the amplitude attribute extracting module 901 extracts the seismic amplitude attribute value of the seismic data of the reservoir to be predicted after demasking, so that the prediction accuracy of the energy storage coefficient can be further improved.

Fig. 11 shows a schematic structural diagram of a conversion relationship between a fit energy storage coefficient and a seismic amplitude attribute value in an energy storage coefficient prediction device for a weathered shell karst reservoir according to an embodiment of the present invention, and for convenience of explanation, only a portion relevant to the embodiment of the present invention is shown, which is described in detail below:

in an embodiment of the present invention, in order to further improve the prediction accuracy of the energy storage coefficient, referring to fig. 11, each unit included in the conversion relationship between the fit energy storage coefficient and the seismic amplitude attribute value is used to perform each step in the corresponding embodiment of fig. 3, and specifically please refer to fig. 3 and the related description in the corresponding embodiment of fig. 3, which will not be repeated herein. In the embodiment of the present invention, the conversion relationship between the fit energy storage coefficient and the seismic amplitude attribute value includes a seismic record determining module 1101, a sample seismic amplitude extracting module 1102, a sample energy storage coefficient determining module 1103 and a conversion relationship fit construction module 1104.

The seismic record determination module 1101 is configured to determine a three-dimensional forward seismic record of the target sample reservoir according to the seismic data of the target sample reservoir.

The sample seismic amplitude extraction module 1102 is configured to extract a seismic amplitude attribute value of a three-dimensional forward seismic record of the target sample reservoir, and a inline sequence number value and a crossline sequence number value corresponding to the seismic amplitude attribute value.

The sample energy storage coefficient determining module 1103 is configured to determine an energy storage coefficient of the target sample reservoir according to the inline serial number value and the crossline serial number value corresponding to the seismic amplitude attribute value.

The conversion relation fitting construction module 1104 is configured to perform intersection analysis on the energy storage coefficient and the seismic amplitude attribute value of the target sample reservoir, and fit and construct a conversion relation between the energy storage coefficient and the seismic amplitude attribute value.

In the embodiment of the invention, the seismic record determining module 1101 determines a three-dimensional forward seismic record of the target sample reservoir according to the seismic data of the target sample reservoir, and then the sample seismic amplitude extracting module 1102 extracts a seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir and a inline sequence number value and a crossline sequence number value corresponding to the seismic amplitude attribute value, then the sample energy storage coefficient determining module 1103 determines an energy storage coefficient of the target sample reservoir according to the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value, and finally the conversion relation fitting constructing module 1104 performs intersection analysis on the energy storage coefficient and the seismic amplitude attribute value of the target sample reservoir, fits to construct a conversion relation between the energy storage coefficient and the seismic amplitude attribute value, and the fitted conversion relation can accurately reflect the association relation between the energy storage coefficient and the seismic amplitude attribute value, predicts the energy storage coefficient by using the conversion relation between the energy storage coefficient and the seismic amplitude attribute value obtained by fitting, and the prediction accuracy of the energy storage coefficient can be further improved.

Fig. 12 shows another schematic structure of a conversion relationship between a fit energy storage coefficient and a seismic amplitude attribute value in an energy storage coefficient prediction apparatus for a weathered shell karst reservoir according to an embodiment of the present invention, and for convenience of explanation, only a portion relevant to the embodiment of the present invention is shown, which is described in detail below:

in an embodiment of the present invention, in order to further improve the prediction accuracy of the energy storage coefficient, referring to fig. 12, each unit included in the conversion relationship between the fit energy storage coefficient and the seismic amplitude attribute value is used to perform each step in the corresponding embodiment of fig. 4, and specifically please refer to fig. 4 and the related description in the corresponding embodiment of fig. 4, which will not be repeated herein. In the embodiment of the present invention, on the basis of the above-mentioned module structure shown in fig. 11, the method further includes a sample de-masking processing module 1201 for fitting the conversion relationship between the energy storage coefficient and the seismic amplitude attribute value.

The sample de-shielding processing module 1201 is configured to perform a de-strong reflection shielding process on the three-dimensional forward seismic record of the target sample reservoir along the weathered crust, so as to obtain a three-dimensional forward seismic record after the target sample reservoir is de-shielded.

The sample seismic amplitude extraction module 1102 is further configured to extract a seismic amplitude attribute value of the three-dimensional forward seismic record after the target sample reservoir is unmasked, and a inline sequence number value and a crossline sequence number value corresponding to the seismic amplitude attribute value.

In the embodiment of the invention, the sample unshielded processing module 1201 performs the unshielded processing on the three-dimensional forward seismic record of the target sample reservoir along the weathered shell to obtain the three-dimensional forward seismic record of the target sample reservoir, and the sample seismic amplitude extracting module 1102 extracts the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir, and the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value, so that the unshielded processing can further improve the prediction precision of the energy storage coefficient.

Fig. 13 shows a schematic structure of a seismic record determining module 1101 in an energy storage coefficient prediction apparatus for a weathered shell karst reservoir according to an embodiment of the present invention, and for convenience of explanation, only a portion related to the embodiment of the present invention is shown, which is described in detail below:

in an embodiment of the present invention, in order to improve the accuracy of determining the three-dimensional forward seismic record of the target sample reservoir, referring to fig. 13, each unit included in the seismic record determining module 1101 is configured to execute each step in the corresponding embodiment of fig. 5, and specifically please refer to fig. 5 and the related description in the corresponding embodiment of fig. 5, which are not repeated herein. In the embodiment of the present invention, the seismic record determining module 1101 includes a seismic data acquiring unit 1301, a wavelet acquiring unit 1302, a model constructing unit 1303 and a forward modeling unit 1304.

A seismic data acquisition unit 1301 configured to acquire seismic data of a target sample reservoir.

A wavelet acquisition unit 1302 for acquiring seismic wavelets of the target sample reservoir from the seismic data of the target sample reservoir.

The model construction unit 1303 is configured to construct a three-dimensional wave impedance model of the target sample reservoir with respect to the reservoir thickness, the reservoir porosity, and the time.

The forward modeling unit 1304 is configured to perform seismic forward modeling by using the constructed three-dimensional wave impedance model and the seismic wavelet of the target sample reservoir, and obtain a three-dimensional forward seismic record of the target sample reservoir.

In the embodiment of the present invention, firstly, the seismic data acquisition unit 1301 acquires the seismic data of the target sample reservoir, then the wavelet acquisition unit 1302 acquires the seismic wavelet of the target sample reservoir according to the seismic data of the target sample reservoir, then the model construction unit 1303 constructs a three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity and time, and finally the forward modeling unit 1304 performs the seismic forward modeling by using the constructed three-dimensional wave impedance model of the target sample reservoir and the seismic wavelet to acquire the three-dimensional forward seismic record of the target sample reservoir.

Fig. 14 shows a schematic structural diagram of a model building unit 1303 in an energy storage coefficient prediction apparatus for a weathered shell karst reservoir according to an embodiment of the present invention, and for convenience of explanation, only a portion related to the embodiment of the present invention is shown, which is described in detail below:

in an embodiment of the present invention, in order to improve the accuracy of constructing the three-dimensional wave impedance model and further improve the prediction accuracy of the energy storage coefficient, referring to fig. 14, each unit included in the model constructing unit 1303 is configured to execute each step in the corresponding embodiment of fig. 6, and specifically please refer to fig. 6 and the related description in the corresponding embodiment of fig. 6, which are not repeated herein. In the embodiment of the present invention, the model construction unit 1303 includes a logging data acquisition subunit 1401, an upper and lower formation wave impedance determination subunit 1402, a karst reservoir wave impedance determination subunit 1403, and a model construction subunit 1404.

A logging data acquisition subunit 1401 is configured to acquire logging data of the target sample reservoir.

An upper and lower formation wave impedance determination subunit 1402 is configured to determine an average wave impedance of an overburden formation and an average wave impedance of an underburden carbonate formation in the target sample reservoir using the log data of the target sample reservoir.

The karst reservoir wave impedance determination subunit 1403 is configured to determine, by using the logging data of the target sample reservoir, wave impedances corresponding to weathered-crust karst reservoirs with different porosities in the target sample reservoir through petrophysical analysis.

The model construction subunit 1404 is configured to establish a three-dimensional wave impedance model of the target sample reservoir with respect to the reservoir thickness, the reservoir porosity and the time according to the average wave impedance of the overburden layer and the average wave impedance of the underlying carbonate layer in the target sample reservoir, and the wave impedances corresponding to the weathered-crust karst reservoirs with different porosities in the target sample reservoir.

In the embodiment of the present invention, firstly, the logging data obtaining subunit 1401 obtains logging data of a target sample reservoir, and then the upper and lower formation wave impedance determining subunit 1402 determines an average wave impedance of an overlying stratum and an average wave impedance of an underlying carbonate stratum in the target sample reservoir by using the logging data of the target sample reservoir, then the karst reservoir wave impedance determining subunit 1403 determines wave impedances corresponding to weathered karst reservoirs with different porosities in the target sample reservoir by using the logging data of the target sample reservoir through petrophysical analysis, and finally the model constructing subunit 1404 establishes a three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity and time according to the average wave impedance of the overlying stratum and the average wave impedance of the underlying carbonate stratum in the target sample reservoir and the average wave impedance corresponding to weathered karst reservoirs with different porosities in the target sample reservoir, and by constructing the three-dimensional wave impedance model with respect to reservoir thickness, reservoir porosity and time, the accuracy of constructing the three-dimensional wave impedance model can be improved, and the prediction accuracy of the energy storage coefficient can be improved.

Fig. 15 shows another schematic structural diagram of a model building unit 1303 in an energy storage coefficient prediction apparatus for a weathered shell karst reservoir according to an embodiment of the present invention, and for convenience of explanation, only a portion related to the embodiment of the present invention is shown, which is described in detail below:

in an embodiment of the present invention, in order to further improve the accuracy of constructing the three-dimensional wave impedance model, referring to fig. 15, each unit included in the model constructing unit 1303 is configured to execute each step in the corresponding embodiment of fig. 7, and detailed descriptions of fig. 7 and the corresponding embodiment of fig. 7 are omitted herein. In the embodiment of the present invention, on the basis of the above-described module structure shown in fig. 14, the model construction unit 1303 further includes a maximum value determination sub-unit 1501.

A maximum determination subunit 1501 is configured to determine a reservoir thickness maximum and a porosity maximum of a weathered shell karst reservoir in a target sample reservoir using log data of the target sample reservoir.

In the embodiment of the invention, the maximum value determination subunit 1501 determines the reservoir thickness maximum value and the porosity maximum value of the weathered shell karst reservoir in the target sample reservoir by using the logging data of the target sample reservoir, so that the accuracy of constructing the three-dimensional wave impedance model can be further improved, and the prediction accuracy of the energy storage coefficient can be further improved.

Fig. 16 shows a schematic structure of a sample seismic amplitude extraction module 1102 in an energy storage coefficient prediction apparatus for a weathered shell karst reservoir according to an embodiment of the present invention, and for convenience of explanation, only the portions relevant to the embodiments of the present invention are shown, which are described in detail below:

in an embodiment of the present invention, in order to improve the accuracy of extracting the seismic amplitude attribute values, referring to fig. 16, each unit included in the sample seismic amplitude extraction module 1102 is configured to perform each step in the corresponding embodiment of fig. 8, and detailed descriptions of fig. 8 and the corresponding embodiment of fig. 8 are omitted herein. In an embodiment of the present invention, the sample seismic amplitude extraction module 1102 includes a response time window determining unit 1601 and a seismic amplitude attribute extracting unit 1602.

A response time window determining unit 1601, configured to determine an effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir; the effective earthquake response time window of the target sample reservoir is the time length of the weathering crust from the corresponding peak reflection bottom of the reservoir on the earthquake channel where the reservoir thickness maximum value and the porosity maximum value are located.

The seismic amplitude attribute extraction unit 1602 is configured to extract, according to a three-dimensional forward seismic record of the target sample reservoir, a seismic amplitude attribute value and a inline sequence number value and a crossline sequence number value corresponding to the seismic amplitude attribute value along an effective seismic response time window of the target sample reservoir.

In the embodiment of the present invention, the response time window determining unit 1601 determines the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir, and the seismic amplitude attribute extracting unit 1602 extracts the seismic amplitude attribute value and the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value along the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir, and extracts the seismic amplitude attribute value along the effective seismic response time window, thereby improving the accuracy of extracting the seismic amplitude attribute value and further improving the prediction accuracy of the energy storage coefficient.

Compared with the method for indirectly predicting the capacity (energy storage coefficient) of the karst reservoir by the aid of paleomorphic restoration and earthquake equality, the method for indirectly predicting the capacity (energy storage coefficient) of the karst reservoir by means of the paleomorphic restoration and earthquake equality, the embodiment of the invention directly realizes quantitative prediction of the energy storage coefficient of the weathered shell karst reservoir by means of establishing a karst reservoir three-dimensional wave impedance model with continuously-changed thickness and porosity and forward seismic record analysis of the karst reservoir three-dimensional wave impedance model and analyzing the intrinsic quantitative relation among the thickness, the porosity and the earthquake of the karst reservoir by means of mechanism analysis.

The existing earthquake prediction methods of the energy storage coefficients are to respectively predict the porosity and the thickness of the reservoir by adopting earthquake data, and then calculate the energy storage coefficients after multiplying the porosity and the thickness. The embodiment of the invention directly realizes the prediction of the energy storage coefficient of the karst reservoir, and the productivity prediction precision is higher. The specific aspects are as follows: firstly, two key factors affecting the capacity of karst reservoirs are considered simultaneously: thickness and porosity; secondly, an internal quantitative relation among thickness, porosity and seismic amplitude attributes is established, reasonable physical significance is given to the seismic attributes, and the seismic information application is more sufficient; and thirdly, the actual seismic reflection of the karst reservoir is recovered by adopting the process of removing strong reflection shielding along the weathered crust, and the weak reflection characteristic of the reservoir is recovered and highlighted so as to better improve the prediction capability.

In summary, in the embodiment of the present invention, the energy storage coefficient of the reservoir to be predicted is obtained by extracting the seismic amplitude attribute value of the seismic data of the reservoir to be predicted and predicting by using the conversion relationship between the energy storage coefficient obtained after fitting and the seismic amplitude attribute value. According to the embodiment of the invention, the energy storage coefficient of the weathered shell karst reservoir is directly predicted by fitting the conversion relation between the energy storage coefficient and the seismic amplitude attribute value, so that the accuracy of the energy storage coefficient prediction of the weathered shell karst reservoir can be improved.

It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.

Claims

1. A method for predicting the energy storage coefficient of a weathered karst reservoir, comprising:

predicting to obtain the energy storage coefficient of the reservoir to be predicted by using the conversion relation between the energy storage coefficient obtained after fitting and the seismic amplitude attribute value;

The method further comprises the steps of:

performing strong reflection removal shielding treatment on the seismic data of the reservoir to be predicted to obtain the seismic data of the reservoir to be predicted after the shielding;

extracting seismic amplitude attribute values of seismic data of a reservoir to be predicted, comprising:

extracting an earthquake amplitude attribute value of the earthquake data of which the reservoir to be predicted is unmasked;

fitting a conversion relationship between the energy storage coefficient and the seismic amplitude attribute value includes:

determining a three-dimensional forward seismic record of the target sample reservoir according to the seismic data of the target sample reservoir;

extracting a seismic amplitude attribute value of a three-dimensional forward seismic record of a target sample reservoir and a inline sequence number value and a crossline sequence number value corresponding to the seismic amplitude attribute value;

determining an energy storage coefficient of a target sample reservoir according to the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value;

performing intersection analysis on the energy storage coefficient and the seismic amplitude attribute value of the target sample reservoir, and fitting to construct a conversion relationship between the energy storage coefficient and the seismic amplitude attribute value;

the conversion relation between the energy storage coefficient and the seismic amplitude attribute value is as follows:

variance R ² ＝0.94；

2. The method of energy storage coefficient prediction for a weathered karst reservoir of claim 1, wherein fitting a conversion relationship between energy storage coefficients and seismic amplitude attribute values further comprises:

performing strong reflection removal shielding treatment on the three-dimensional forward seismic record of the target sample reservoir along the weathered shell to obtain the three-dimensional forward seismic record of the target sample reservoir after the shielding;

extracting a seismic amplitude attribute value of a three-dimensional forward seismic record of a target sample reservoir and a inline sequence number value and a crossline sequence number value corresponding to the seismic amplitude attribute value, including:

and extracting the seismic amplitude attribute value of the three-dimensional forward seismic record after the target sample reservoir is unmasked, and the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value.

3. The method of claim 1, wherein determining a three-dimensional forward seismic record of the target sample reservoir from the seismic data of the target sample reservoir comprises:

acquiring seismic data of a target sample reservoir;

acquiring seismic wavelets of the target sample reservoir according to the seismic data of the target sample reservoir;

constructing a three-dimensional wave impedance model of a target sample reservoir with respect to reservoir thickness, reservoir porosity and time;

And carrying out seismic forward modeling by using the constructed three-dimensional wave impedance model and the seismic wavelets of the target sample reservoir to obtain a three-dimensional forward seismic record of the target sample reservoir.

4. The method of claim 3, wherein constructing a three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity, and time comprises:

acquiring logging data of a target sample reservoir;

determining an average wave impedance of an overburden formation and an average wave impedance of an underlying carbonate formation in the target sample reservoir using the log data of the target sample reservoir;

determining wave impedance corresponding to weathered crust karst reservoirs with different porosities in the target sample reservoir through petrophysical analysis by using logging data of the target sample reservoir;

and establishing a three-dimensional wave impedance model of the target sample reservoir relative to the reservoir thickness, the reservoir porosity and the time according to the average wave impedance of the overlying stratum in the target sample reservoir and the average wave impedance of the underlying carbonate stratum and the wave impedance corresponding to the weathered crust karst reservoirs with different porosities in the target sample reservoir.

5. The method of claim 4, wherein constructing a three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity, and time further comprises:

Determining a reservoir thickness maximum value and a porosity maximum value of the weathered shell karst reservoir in the target sample reservoir by using the logging data of the target sample reservoir;

6. The method of claim 1, wherein extracting the seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir and the inline and crossline sequence values corresponding to the seismic amplitude attribute value comprises:

determining an effective earthquake response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir; the effective earthquake response time window of the target sample reservoir is the time length of the weathering crust from the corresponding peak reflection bottom of the reservoir on the earthquake path with the maximum reservoir thickness and the maximum porosity;

And extracting the seismic amplitude attribute value and the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value along the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir.

7. An energy storage coefficient prediction device for a weathered karst reservoir, comprising:

the energy storage coefficient prediction module is used for predicting and obtaining the energy storage coefficient of the reservoir to be predicted by utilizing the conversion relation between the energy storage coefficient obtained after fitting and the seismic amplitude attribute value;

the device further comprises:

the demasking processing module is used for performing the demasking processing of the seismic data of the reservoir to be predicted to obtain the seismic data of the reservoir to be predicted after demasking;

the amplitude attribute extraction module is also used for extracting the seismic amplitude attribute value of the seismic data of which the reservoir to be predicted is subjected to the de-shielding;

fitting a conversion relationship between the energy storage coefficient and the seismic amplitude attribute value, comprising:

the seismic record determining module is used for determining a three-dimensional forward seismic record of the target sample reservoir according to the seismic data of the target sample reservoir;

The sample seismic amplitude extraction module is used for extracting a seismic amplitude attribute value of the three-dimensional forward seismic record of the target sample reservoir and a longitudinal line serial number value and a transverse line serial number value corresponding to the seismic amplitude attribute value;

the sample energy storage coefficient determining module is used for determining the energy storage coefficient of the target sample reservoir according to the inline serial number value and the crossline serial number value corresponding to the seismic amplitude attribute value;

the conversion relation fitting construction module is used for carrying out intersection analysis on the energy storage coefficient and the seismic amplitude attribute value of the target sample reservoir, and fitting and constructing the conversion relation between the energy storage coefficient and the seismic amplitude attribute value;

variance R ² ＝0.94；

8. The device for predicting the energy storage coefficient of a weathered karst reservoir of claim 7, wherein fitting a conversion relationship between the energy storage coefficient and the seismic amplitude attribute value further comprises:

the sample de-shielding processing module is used for performing de-strong reflection shielding processing on the three-dimensional forward seismic record of the target sample reservoir along the weathered shell to obtain the three-dimensional forward seismic record of the target sample reservoir after de-shielding;

The sample seismic amplitude extraction module is also used for extracting the seismic amplitude attribute value of the three-dimensional forward seismic record after the target sample reservoir is subjected to shielding, and the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value.

9. The device for predicting the energy storage coefficient of a weathered karst reservoir of claim 7, wherein the seismic record determination module comprises:

the seismic data acquisition unit is used for acquiring the seismic data of the target sample reservoir;

the wavelet acquisition unit is used for acquiring the seismic wavelet of the target sample reservoir according to the seismic data of the target sample reservoir;

the model construction unit is used for constructing a three-dimensional wave impedance model of the target sample reservoir with respect to reservoir thickness, reservoir porosity and time;

the forward modeling unit is used for performing seismic forward modeling by using the constructed three-dimensional wave impedance model and the seismic wavelet of the target sample reservoir to obtain a three-dimensional forward seismic record of the target sample reservoir.

10. The apparatus for predicting the energy storage coefficient of a weathered karst reservoir according to claim 9, wherein the model building unit includes:

a logging data acquisition subunit, configured to acquire logging data of a target sample reservoir;

An upper and lower formation wave impedance determination subunit configured to determine an average wave impedance of an overburden formation and an average wave impedance of an underburden carbonate formation in the target sample reservoir using the log data of the target sample reservoir;

the karst reservoir wave impedance determining subunit is used for determining the wave impedance corresponding to the weathered karst reservoirs with different porosities in the target sample reservoir through petrophysical analysis by using the logging data of the target sample reservoir;

the model construction subunit is used for establishing a three-dimensional wave impedance model of the target sample reservoir relative to the reservoir thickness, the reservoir porosity and the time according to the average wave impedance of the overlying stratum in the target sample reservoir and the average wave impedance of the underlying carbonate stratum and the wave impedances corresponding to the weathered karst reservoirs with different porosities in the target sample reservoir.

11. The apparatus for predicting the energy storage coefficient of a weathered karst reservoir according to claim 10, wherein the model building unit further comprises:

a maximum value determination subunit, configured to determine a reservoir thickness maximum value and a porosity maximum value of the weathered shell karst reservoir in the target sample reservoir using the logging data of the target sample reservoir;

12. The device for predicting the energy storage coefficient of a weathered karst reservoir of claim 7, wherein the sample seismic amplitude extraction module comprises:

the response time window determining unit is used for determining an effective earthquake response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir; the effective earthquake response time window of the target sample reservoir is the time length of the weathering crust from the corresponding peak reflection bottom of the reservoir on the earthquake path with the maximum reservoir thickness and the maximum porosity;

the seismic amplitude attribute extraction unit is used for extracting the seismic amplitude attribute value and the inline sequence number value and the crossline sequence number value corresponding to the seismic amplitude attribute value along the effective seismic response time window of the target sample reservoir according to the three-dimensional forward seismic record of the target sample reservoir.

13. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein execution of the computer program by the processor implements the method of predicting the energy storage coefficient of a weathered karst reservoir according to any one of claims 1 to 6.

14. A computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for performing the method for predicting the energy storage coefficient of a weathered karst reservoir according to any one of claims 1 to 6.